dataxray

An Interactive Table Interface for Data Summaries

Stephanie Lussier
Agustin Calatroni

useR! 2022: Session 20, Data Visualization
Wednesday, 22 June 2022

Why review data?

Outliers¹

Erroneous data²

Unexpected covariates

Missing data³

Hmisc::describe

A modern framework

plotly ⁴

reactable ⁵

crosstalk ⁶

Instructions

• Create xray object
• Display xray

library(dataxray)

gtsummary::trial %>%
  make_xray()

Instructions

• Create xray object
• Display xray

library(dataxray)

gtsummary::trial %>%
  make_xray() %>%
  view_xray()

Instructions

gtsummary::trial %>%
  report_xray(data_name = "trial", study = "gtsummary")

Metrics

group_by

adlb <- read_xpt(str_glue("https://raw.githubusercontent.com/phuse-org/phuse-scripts/master/data/adam/cdiscpilot01/adlbc.xpt")) 

adlb %>%
  report_xray(by = "PARAM", 
              study = "PHUSE", 
              data_name = "ADLB")

Next Steps

CRAN release coming soon!

devtools::install_github("agstn/dataxray")

Acknowledgements:

Hmisc::describe()

Agustin Calatroni and Becca Krouse

Footnotes

1. bookdown.org/dli/rguide/

2. statisticsbyjim.com

3. r-cubed.rostools.org/

4. plotly-r.com

5. glin.github.io/reactable

6. rstudio.github.io/crosstalk